The primary goal of this research is to develop anew software tool to help epidemiologists, biostatisticians, and other scientists recognized patterns in multi-dimensional spatial data. The focus of the Phase I project was on the exploration of geographic patterns in cancer data, including specifically correlations between different types of cancer and correlations with environmental variables. Major accomplishments in Phase I were to identify key requirements for effective visualization and analysis of spatially-related disease data, and to prototype and approach and a set of techniques that address these requirements. The project used object-oriented methodologies to create a customizable software framework. The proposed Phase II work will build on this base to develop a full software system that can be evaluated and refined through collaboration with scientists at several "beta test" sites. The major technical innovation in this project is the development of new object-oriented software to explore geographically-linked statistical data. The major health-related contribution is an enhanced ability to find clues to etiology through better tools for detecting patterns in the geographic distribution of disease incidence and correlating them with environmental, demographic, and other factors.